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Results for “structured dynamic model tuning”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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207 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Can a simple topological-constraints-based model predict the initial dissolution rate of borosilicate and aluminosilicate glasses?

Tuning glass composition to obtain targeted properties generally relies on empirical approaches. However, a deep understanding of the physical and chemical mechanisms linking glass composition to its structure and properties would enable developing reliable predictive models. Indeed, although empirical models are usually able to interpolate composition–property relationships within a given compositional envelope, they often fail at extrapolating predictions far from their training domain. Here, as an alternative route to empirical models, we show that a structural descriptor based on the number of topological constraints per atom can be used to predict the initial dissolution rate of aluminosilicate and borosilicate glasses after being parameterized on different families of glasses (specific series of borosilicate glasses). Sixteen glasses belonging to these families were studied and their initial dissolution rates were determined at 90 °C and pH 90 °C = 9, covering rates spanning over 5 orders of magnitude. The model based on topological constraints was trained based on seven select borosilicate glasses (R 2 = 0.997) and used to predict the dissolution rate of nine additional borosilicate and aluminosilicate glasses. We show that, provided that corrections are made for high alkali content glasses that dissolve incongruently (preferential release of Na), the model gives reasonable predictions, even far from its training domain.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Results of the second Ice Shelf–Ocean Model Intercomparison Project (ISOMIP+)

Ocean-driven basal melting of Antarctic ice shelves plays an important role in the mass loss of the Antarctic Ice Sheet. Ice shelf cavity-resolving ocean models are a valuable tool for understanding ice shelf-ocean interactions and for simulating projections of ice shelf and ocean states under future climate. Designed to assess the current state of ice shelf–ocean modelling, the second Ice Shelf–Ocean Model Intercomparison Project, ISOMIP+, consists of 12 ocean model configurations submitted with a common, idealised experimental setup. Here, we focus on the experiments Ocean0–2 (Asay-Davis et al., 2016), which are ocean models with idealised, static ice shelf geometries, but where the ocean reaches a balance with prescribed far-field ocean conditions. Different thermal transfer coefficient values (ranging from 0.011 to 0.2) are used for each model in the melting parameterisation to achieve a common, tuned melt rate since the models cover a range of types of vertical coordinates, ice–ocean boundary layer treatments, and numerical schemes. These model differences lead to spread in the resultant ocean properties, circulation, boundary-layer structure and spatial distribution of melting. We also highlight similarities between models, such as a shared linear relationship across most models between melt rate and overturning and barotropic streamfunctions during the spin-up and spin-down, demonstrating a robust relationship between melt and circulation across models and forcing conditions. The ISOMIP+ results provide a systematic comparison of ice shelf cavity-capable ocean models. However, we also demonstrate the need for realistic ice shelf–ocean model intercomparison projects (some already underway) to assess model biases and inter-model variation against sparse observations. Further research is needed to understand the differences between models and further improve our modelled representations of the ice–ocean boundary layer and ice shelf cavity circulation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2005

Generic Kalman Filter Software

The Generic Kalman Filter (GKF) software provides a standard basis for the development of application-specific Kalman-filter programs. Historically, Kalman filters have been implemented by customized programs that must be written, coded, and debugged anew for each unique application, then tested and tuned with simulated or actual measurement data. Total development times for typical Kalman-filter application programs have ranged from months to weeks. The GKF software can simplify the development process and reduce the development time by eliminating the need to re-create the fundamental implementation of the Kalman filter for each new application. The GKF software is written in the ANSI C programming language. It contains a generic Kalman-filter-development directory that, in turn, contains a code for a generic Kalman filter function; more specifically, it contains a generically designed and generically coded implementation of linear, linearized, and extended Kalman filtering algorithms, including algorithms for state- and covariance-update and -propagation functions. The mathematical theory that underlies the algorithms is well known and has been reported extensively in the open technical literature. Also contained in the directory are a header file that defines generic Kalman-filter data structures and prototype functions and template versions of application-specific subfunction and calling navigation/estimation routine code and headers. Once the user has provided a calling routine and the required application-specific subfunctions, the application-specific Kalman-filter software can be compiled and executed immediately. During execution, the generic Kalman-filter function is called from a higher-level navigation or estimation routine that preprocesses measurement data and post-processes output data. The generic Kalman-filter function uses the aforementioned data structures and five implementation- specific subfunctions, which have been developed by the user on the basis of the aforementioned templates. The GKF software can be used to develop many different types of unfactorized Kalman filters. A developer can choose to implement either a linearized or an extended Kalman filter algorithm, without having to modify the GKF software. Control dynamics can be taken into account or neglected in the filter-dynamics model. Filter programs developed by use of the GKF software can be made to propagate equations of motion for linear or nonlinear dynamical systems that are deterministic or stochastic. In addition, filter programs can be made to operate in user-selectable "covariance analysis" and "propagation-only" modes that are useful in design and development stages.

Lisano, Michael E., II↗
DOE OSTI2024

Accelerated Steam Methane Reforming by Dynamically Applied Charges

Catalyst design has traditionally focused on tuning active site properties to optimally bind reaction intermediates and balance the kinetic requirements of multiple competing chemical processes, as necessitated by the Sabatier principle. It has recently been proposed that for reactions following certain potential energy landscapes, the activity limit imposed by the Sabatier principle may be overcome by using programmed oscillations of surface electron density at the timescales of surface reactions (i.e., “catalytic resonance”). Here, we use a combination of density functional theory (DFT) simulations and transient kinetic models (TKMs) to simulate the kinetics of steam methane reforming (SMR) on Ru(211) surfaces under statically and dynamically applied charges. DFT-calculated binding energies of SMR intermediates and transition states exhibit strong sensitivity to positively applied charges and follow unique scaling relationships that deviate from linear periodic trends across transition metals. Our simulations demonstrate that applying a small positive charge to Ru dramatically enhances the steady-state turnover frequency (TOF) of SMR by up to 5 orders of magnitude above the TOF observed over neutral Ru. Thus, statically charging Ru catalysts may be an effective strategy to lower the temperature requirements for SMR. Dynamic square-wave oscillations in charge resulted in SMR catalytic resonance with an onset frequency f ∼ 106 Hz and the corresponding average TOFs exceeding the statically charged Ru surface by an additional 15%. Here, based on sensitivity analyses performed for the two end points of oscillation, we propose that dynamic TOF improvement beyond the Sabatier maximum can be expected when the system oscillates between two kinetic regimes that are uniquely controlled by distinct elementary steps.

Catalysts↗
DOE OSTI2025

Machine learning-accelerated path integral molecular dynamics simulations of reactive organic electrolytes

Hydrogen bonded electrolytes that exhibit accelerated proton transport via sequential reactive hops have drawn interest for their promise in clean energy applications. Molecular dynamics simulations of these electrolytes offer the opportunity to uncover microscopic mechanistic details that could be used to design and tune the properties of candidate electrolyte technologies. However, accurately modeling the proton transfer reactions and transport properties that give rise to high charge conductivites in these electrolytes proves computationally challenging because of the need to perform lengthy condensed phase simulations, treating both the electronic and nuclear degrees of freedom quantum mechanically. In this paper, we demonstrate that such a modeling task can be efficiently achieved with the use of density functional theory (DFT)-trained machine learning potentials (MLP) to accelerate path integral molecular dynamics (PIMD) simulations. We highlight the practical utility of this approach by using it to benchmark how closely PIMD simulations employing different DFT exchange–correlation functionals reproduce the composition-dependent densities, diffusion coefficients, and electrical conductivities of mixtures consisting of imidazole and levulinic acid. Even with the speedup afforded by our MLPs, PIMD simulations remain quite expensive. Furthermore, in order to render PIMD more computationally tractable, we introduce and benchmark the accuracy of a ring polymer contraction approach that leverages a computationally efficient short-range MLP to accelerate our PIMD simulations by an additional factor of four.

Chemical bonding↗
DOE OSTI2024

Structural and mechanical properties of monolayer amorphous carbon and boron nitride

Amorphous materials exhibit various characteristics that are not featured by crystals and can sometimes be tuned by their degree of disorder (DOD). Here, we report results on the mechanical properties of monolayer amorphous carbon (MAC) and monolayer amorphous boron nitride (maBN) with different DOD. The pertinent structures are obtained by kinetic-Monte-Carlo (kMC) simulations using machine-learning potentials (MLP) with density-functional-theory (DFT)-level accuracy. An intuitive order parameter, namely the areal fraction F x occupied by crystallites within the continuous random network, is proposed to describe the DOD. We find that F x captures the essence of the DOD: Samples with the same F x but different sizes and arrangements of crystallites, obtained using two distinct kMC procedures, have virtually identical radial distributions functions as well as bond-length and bond-angle distributions. Furthermore, by simulating the fracture process with molecular dynamics, we found that the mechanical responses of MAC and maBN before fracture are mainly determined by F x and are insensitive to the sizes and specific arrangements and to some extent the numbers and area distributions of the crystallites. The behavior of cracks in the two materials is analyzed and found to mainly propagate in meandering paths in the CRN region and to be influenced by crystallites in distinct ways that toughen the material. Furthermore, the present results reveal the relation between structure and mechanical properties in amorphous monolayers and may provide a universal toughening strategy for 2D materials.

2-dimensional systems↗
DOE OSTI2025

Dynamics of McMillan mappings II. axially symmetric map

Here, in this article, we investigate the transverse dynamics of a single particle in a model integrable accelerator lattice, based on a McMillan axially-symmetric electron lens. Although the McMillan e-lens has been considered as a device potentially capable of mitigating collective space charge forces, some of its fundamental properties have not been described yet. The main goal of our work is to close this gap and understand the limitations and potentials of this device. It is worth mentioning that the McMillan axially symmetric map provides the first-order approximations of dynamics for a general linear lattice plus an arbitrary thin lens with motion separable in polar coordinates. Therefore, advancements in its understanding should give us a better picture of more generic and not necessarily integrable round beams. In the first part of the article, we classify all possible regimes with stable trajectories and find the canonical action-angle variables. This provides an evaluation of the dynamical aperture, Poincaré rotation numbers as functions of amplitudes, and thus determines the spread in nonlinear tunes. Also, we provide a parameterization of invariant curves, allowing for the immediate determination of the map image forward and backward in time. The second part investigates the particle dynamics as a function of system parameters. We show that there are three fundamentally different configurations of the accelerator optics causing different regimes of nonlinear oscillations. Each regime is considered in great detail, including the limiting cases of large and small amplitudes. In addition, we analyze the dynamics in Cartesian coordinates and provide a description of observable variables and corresponding spectra.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Progress on Computational Modeling of Water-Based NSTF (FY2021)

This report documents the FY21 progress and achievements made in the computational analyses of the water-based NSTF. Both system-level and high-fidelity Computational Fluid Dynamics (CFD) analyses were performed to gain a complete understanding of the complex flow and heat transfer phenomena in natural convection systems. The progress on the waterbased NSTF experimental testing is summarized in a companion report (ANL-ART-230). As a continuation of progress from previous years, in FY21 the RELAP5 model of the NSTF was first updated to include a representative heated cavity that incorporated convection and conduction means of heat transfer. Two different cavity models were developed, one that models the radiation heat exchange among all surfaces in one enclosure (Cavity Model 1), and another that employs multiple radiation enclosures with each considering the surfaces at one axial level (Cavity Model 2). This updated RELAP5 deck was benchmarked with single-phase test data to tune form loss coefficients of the elbows and tees, along with heat transfer coefficients within the cavity and off the external insulation panels. This tuned model was then found to accurately predict fluid temperatures within 2.5% and both system and riser flow rates within 6% during single-phase, steady-state simulations. For transient simulations, there is a slight over prediction of the flow rate, fluid temperatures, and heater temperatures during the heat-up period, which indicate that the transient heat loss may be underestimated. Following, the capabilities of RELAP5-3D were examined, which feature a conduction enclosure model that is not present in the current version of RELAP5-MOD3.3 used for all previous NSTF simulations. As an initial comparison of the two codes, single-phase simulations were run that used similar input decks. The results indicate that the single-phase flow predicted by the two codes was very similar, however RELAP5-3D appears to predict a higher system flow during the two-phase transient when compared to the flow rates predicted by RELAP5-MOD3.3. Furthermore, RELAP5-3D run did not capture the density wave oscillations or geysering phenomena, which are large oscillation flow instabilities observed in the experimental facility. To further the prediction capabilities for capturing two-phase instabilities, Options 55, 57, 58, 61, which are implemented by default in RELAP5-MOD3.3 but not in RELAP5-3D, were investigated. When enabling Option 61, RELAP5-3D agrees well with MOD3.3 in predicting the total system flow, while other options have negligible effect on the predicted total system flow by RELAP5-3D. However, none of these options enables RELAP5-3D to produce the same flow instabilities. For future steps, efforts are currently underway to investigate RELAP5-3D’s different behavior in predicting low-pressure two-phase instabilities. STAR-CCM+ was used to perform CFD analysis of the water-based test facility and provide simulation results for comparisons to experimental data. Efforts first focused on describing the characteristics of flow within the heated cavity. A study was performed on whether possible leakage flow between the two sides of the cavity could substantially impact and explain the results. An additional second assumption was examined which defined adiabatic side walls, so physical insulation structures were added to the models to allow conduction across this outer insulation. The results suggest that potential porosity of the insulation could be a major factor in the temperature distribution within the cavity and should be considered in any studies where it is desirable to know the cavity wall temperatures to higher accuracy.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗